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Ancestry-Specific Associations Identified in Genome-Wide Combined-Phenotype Study of Red Blood Cell Traits Emphasize Benefits of Diversity in Genomics Chani J

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Ancestry-Specific Associations Identified in Genome-Wide Combined-Phenotype Study of Red Blood Cell Traits Emphasize Benefits of Diversity in Genomics Chani J Hodonsky et al. BMC Genomics (2020) 21:228 https://doi.org/10.1186/s12864-020-6626-9 RESEARCH ARTICLE Open Access Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics Chani J. Hodonsky1,2* , Antoine R. Baldassari1, Stephanie A. Bien3, Laura M. Raffield4, Heather M. Highland1, Colleen M. Sitlani5, Genevieve L. Wojcik6, Ran Tao7, Marielisa Graff1, Weihong Tang8, Bharat Thyagarajan8, Steve Buyske9, Myriam Fornage10, Lucia A. Hindorff11, Yun Li1, Danyu Lin1, Alex P. Reiner3,12, Kari E. North1,4, Ruth J. F. Loos13, Charles Kooperberg12 and Christy L. Avery1 Abstract Background: Quantitative red blood cell (RBC) traits are highly polygenic clinically relevant traits, with approximately 500 reported GWAS loci. The majority of RBC trait GWAS have been performed in European- or East Asian-ancestry populations, despite evidence that rare or ancestry-specific variation contributes substantially to RBC trait heritability. Recently developed combined-phenotype methods which leverage genetic trait correlation to improve statistical power have not yet been applied to these traits. Here we leveraged correlation of seven quantitative RBC traits in performing a combined-phenotype analysis in a multi-ethnic study population. Results: We used the adaptive sum of powered scores (aSPU) test to assess combined-phenotype associations between ~ 21 million SNPs and seven RBC traits in a multi-ethnic population (maximum n = 67,885 participants; 24% African American, 30% Hispanic/Latino, and 43% European American; 76% female). Thirty-nine loci in our multi- ethnic population contained at least one significant association signal (p < 5E-9), with lead SNPs at nine loci significantly associated with three or more RBC traits. A majority of the lead SNPs were common (MAF > 5%) across all ancestral populations. Nineteen additional independent association signals were identified at seven known loci (HFE, KIT, HBS1L/MYB, CITED2/FILNC1, ABO, HBA1/2, and PLIN4/5). For example, the HBA1/2 locus contained 14 conditionally independent association signals, 11 of which were previously unreported and are specific to African and Amerindian ancestries. One variant in this region was common in all ancestries, but exhibited a narrower LD block in African Americans than European Americans or Hispanics/Latinos. GTEx eQTL analysis of all independent lead SNPs yielded 31 significant associations in relevant tissues, over half of which were not at the gene immediately proximal to the lead SNP. (Continued on next page) * Correspondence: [email protected] 1University of North Carolina Gillings School of Public Health, 135 Dauer Dr, Chapel Hill, NC 27599, USA 2University of Virginia Center for Public Health Genomics, 1355 Lee St, Charlottesville, VA 22908, USA Full list of author information is available at the end of the article © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Hodonsky et al. BMC Genomics (2020) 21:228 Page 2 of 14 (Continued from previous page) Conclusion: This work identified seven loci containing multiple independent association signals for RBC traits using a combined-phenotype approach, which may improve discovery in genetically correlated traits. Highly complex genetic architecture at the HBA1/2 locus was only revealed by the inclusion of African Americans and Hispanics/ Latinos, underscoring the continued importance of expanding large GWAS to include ancestrally diverse populations. Keywords: Blood cell traits, Combined-phenotype analysis, Pleiotropy, Diversity, Multi-ethnic, GWAS Background ancestrally diverse Population Architecture using Genomics In the average adult, 200 billion red blood cells (RBCs) are and Epidemiology (PAGE) study [46]. Our findings reinforce generated daily from hematopoietic stem cells in the bone the necessity of incorporating multi-ethnic study populations marrow. The most commonly assessed traits for mature in genomics in order to accurately characterize RBC trait loci RBCs are hematocrit (HCT), hemoglobin concentration and encourage equitable application of the results to transla- (HGB), mean corpuscular hemoglobin (MCH), MCH con- tional work [39]. The complexity of association signals at loci centration (MCHC), mean corpuscular volume (MCV), previously characterized in European- and East Asian- RBC count (RBCC), and red cell distribution width (RDW); ancestry populations also demonstrates improved power to together, these traits are used to characterize RBC develop- perform conditional analysis using a combined-phenotype ment and function, diagnose anemic disorders, and identify model [47]. risk factors for complex chronic diseases [1–6]. RBC traits also are moderately to highly heritable, making these com- Results plex quantitative traits excellent candidates for genomic in- The number of participants with both phenotype and terrogation [7–9]. Improved characterization of RBC genotype data ranged from 33,549 (RDW) to 67,885 molecular pathways has benefitted both disease diagnosis (HCT, see Methods, Tables S2 &S3). Seventy-eight per- and pharmaceutical development, as has been demon- cent of participants were female and participants were strated by recent successes in a BCL11A-silencing gene on average 57 years old at time of blood collection therapy clinical trial for individuals with sickle cell disease (Table S4). Self-reported race/ethnicity in the total study (SCD) [10, 11]. population was approximately 20% African American, Genetic association studies have reported over 500 in- 30% Hispanic/Latino, and 40% European American dependent loci for RBC traits [12–31]. However, several (Table S3). research gaps remain which may be addressed via re- cently developed methods and broadly representative Combined-phenotype analyses study populations. First, previously published RBC trait Approximately 21 M SNPs met our inclusion criteria and genome-wide association study (GWAS) populations were evaluated in our primary analysis, a combined- – have mostly been ancestrally homogeneous [31 39]. phenotype multi-ethnic meta-analysis of seven RBC traits. Utilization of diverse study populations can improve SNP associations with the combined phenotype multi- identification of rare or ancestry-specific variants located ethnic meta-analysis exceeded genome-wide significance in biological pathways that affect phenotypes in global at 39 loci (p <5E-09,FiguresS1,S2), all of which were populations and, when summary data are made publicly identified previously. Lead SNPs at nine loci (KIT, HFE, available, enable construction of broadly applicable poly- HBS1L/MYB, IKZF1, TFR2, HBB, HBA1/2, GCDH, and genic risk scores [40]. Relatedly, gaps between estimated TMPRSS6) were associated with three or more RBC traits heritability and the proportion of variance explained by at genome-wide significance (Tables 1,S5A). HCT, HGB, GWAS findings suggest that additional associations re- and MCHC exhibited genome-wide-significant associa- main to be identified, including rare variants and inde- tions at the fewest loci (eleven, ten, and six, respectively), pendent secondary associations at known loci that are whereas MCH and MCV had the most (twenty and both more likely to be ancestrally specific [12, 41, 42]. twenty-one, respectively, Fig. 1a, Table S5A). Estimated Finally, RBC traits exhibit modest to high correlation, partial correlations by RBC trait pair ranged from HCT- and several dozen loci have been reported for two or MCHC (partial correlation ρ = − 0.02) to HCT-HGB (ρ = more RBC traits, although few studies have leveraged 0.94, Fig. 1b). Consistent with other GWAS of quantitative this shared genetic architecture to increase statistical complex traits, effect size was inversely correlated to allele – power to map novel RBC trait loci [12, 20, 26, 43 45]. frequency across all phenotypes (Fig. 1c). In this work, we examined the individual and shared gen- Trait-specific directions of effect were largely consistent etic architecture of seven RBC traits in participants of the with pairwise correlations. Among 58 independent Hodonsky Table 1 RBC trait loci with evidence of multiple independent signals among PAGE study participants Signal Chr:pos Ref/ CAFa p values Alt a Multi-ethnic RBC trait-specific Combined phenotype by race/ethnicity et al. BMC Genomics AA HL EU HCT HGB MCH MCHC MCV RBCC RDW AA HL EU N = 67,885 N = 67,870 N = 41,317 N = 67,856 N = 41,276 N = 41,310 N = 33,549 N = 16,802 N = 20,697 N = 29,513 HFE locus rs2032451 1 6:26092170
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